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← Human adaptability is fundamentally linked to the efficient…
14 connected korrents · 10 moments on record from 4 Mar 2022 to 4 Sept 2026.
Everything filed under world models
world models
Everything filed under recursive self-improvement
recursive self-improvement
Everything filed under scaling laws
scaling laws
Everything filed under LLMs
LLMs Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: Human adaptability is fundamentally linked to the efficient construction and refinement of internal world models Human adaptability is fundamentally linked to the efficient construction and refinement of internal world models Last stated a year ago
17 Jul 2025
FC
François Chollet — holds since 2025-07-17 — tap for who they are
Same subject: An adaptive agent's world model cannot be a static representation learned once and fixed — tap to centre the map on it An adaptive agent's world model cannot be a static representation learned once and fixed Last stated a year ago
17 Jul 2025
FC
François Chollet — holds since 2025-07-17 — tap for who they are
Same subject: Coding is not just another application domain for AI; it is the meta-skill that lets AI generate its own training material and start the recursive self-improvement loop. — tap to centre the map on it Coding is not just another application domain for AI; it is the meta-skill that lets AI generate its own training material and start the recursive self-improvement loop. Last stated a month ago
10 Aug 2026
FC
François Chollet — holds since 2026-08-10 — tap for who they are
Same subject: Current AI evaluation of world models is too narrow, favoring static representations learned from massive datasets over efficient learning through interaction — tap to centre the map on it Current AI evaluation of world models is too narrow, favoring static representations learned from massive datasets over efficient learning through interaction Last stated a year ago
17 Jul 2025
FC
François Chollet — holds since 2025-07-17 — tap for who they are
Same subject: Games are particularly rich and controlled environments uniquely well-suited for evaluating rapid world model induction in AI — tap to centre the map on it Games are particularly rich and controlled environments uniquely well-suited for evaluating rapid world model induction in AI Last stated a year ago
17 Jul 2025
FC
François Chollet — holds since 2025-07-17 — tap for who they are
Same subject: Rapid world model induction will be critical for achieving robust, general AI that functions in complex, fast-changing real and human worlds — tap to centre the map on it Rapid world model induction will be critical for achieving robust, general AI that functions in complex, fast-changing real and human worlds Last stated a year ago
17 Jul 2025
FC
François Chollet — holds since 2025-07-17 — tap for who they are
Same subject: The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. — tap to centre the map on it The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. Last stated 6 days ago
4 Sept 2026
FL
Fei-Fei Li — holds since 2026-09-04 — tap for who they are
Same subject: Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. — tap to centre the map on it Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. Last stated 12 months ago
12 Sept 2025
SL
Sergey Levine — holds since 2025-09-12 — tap for who they are
Same subject: Fine-tuning with human feedback is a promising direction for aligning language models with human intent. — tap to centre the map on it Fine-tuning with human feedback is a promising direction for aligning language models with human intent. Last stated 5 years ago
4 Mar 2022
JL
Jan Leike — holds since 2022-03-04 — tap for who they are
Same subject: AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started. — tap to centre the map on it AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started. Last stated a month ago
3 Aug 2026
CP
Chamath Palihapitiya — holds since 2026-08-03 — tap for who they are
Same subject: AI research will be fully automated around 2030 or 2031, and AI will beat humans at essentially any job by about 2033. — tap to centre the map on it AI research will be fully automated around 2030 or 2031, and AI will beat humans at essentially any job by about 2033. Last stated 4 weeks ago
11 Aug 2026
RG
Ryan Greenblatt — holds since 2026-08-11 — tap for who they are
Same subject: AI takeover is not the thing to worry about: physical constraints bound recursive self-improvement, and humans reliably act once a risk becomes immediate. — tap to centre the map on it AI takeover is not the thing to worry about: physical constraints bound recursive self-improvement, and humans reliably act once a risk becomes immediate. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. — tap to centre the map on it A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. Last stated 2 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. — tap to centre the map on it A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. Last stated 6 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
Same subject: A model's capability is now a function of how much money you spend on it, so asking what a model can do means nothing until you name a budget. — tap to centre the map on it A model's capability is now a function of how much money you spend on it, so asking what a model can do means nothing until you name a budget. Last stated 2 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
At the centre
Human adaptability is fundamentally linked to the efficient construction and refinement of internal world models
Holds Read this korrent →
An adaptive agent's world model cannot be a static representation learned once and fixed
Holds
Coding is not just another application domain for AI; it is the meta-skill that lets AI generate its own training material and start the recursive self-improvement loop.
Holds
Current AI evaluation of world models is too narrow, favoring static representations learned from massive datasets over efficient learning through interaction
Holds
Games are particularly rich and controlled environments uniquely well-suited for evaluating rapid world model induction in AI
Holds
Rapid world model induction will be critical for achieving robust, general AI that functions in complex, fast-changing real and human worlds
Holds
The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture.
Holds FL Fei-Fei Li
Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff.
Holds SL Sergey Levine
Fine-tuning with human feedback is a promising direction for aligning language models with human intent.
Holds JL Jan Leike
AI is already inside the recursive self-improvement loop — what the labs have shipped in recent weeks shows the cycle has started.
Holds CP Chamath Palihapitiya
AI research will be fully automated around 2030 or 2031, and AI will beat humans at essentially any job by about 2033.
Holds RG Ryan Greenblatt
AI takeover is not the thing to worry about: physical constraints bound recursive self-improvement, and humans reliably act once a risk becomes immediate.
Holds NL Nathan Lambert
A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number.
Holds NB Noam Brown
A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from.
Holds DP Dylan Patel
A model's capability is now a function of how much money you spend on it, so asking what a model can do means nothing until you name a budget.
Holds NB Noam Brown